@article{zhang_sabir_das_2023, title={Speaker Orientation-Aware Privacy Control to Thwart Misactivation of Voice Assistants}, ISSN={["1530-0889"]}, DOI={10.1109/DSN58367.2023.00061}, abstractNote={Smart home voice assistants (VAs) such as Amazon Echo and Google Home have become popular because of the convenience they provide through voice commands. VAs continuously listen to detect the wake command and send the subsequent audio data to the manufacturer-owned cloud service for processing to identify actionable commands. However, research has shown that VAs are prone to replay attack and accidental activations when the wake words are spoken in the background (either by a human or played through a mechanical speaker). Existing privacy controls are not effective in preventing such misactivations. This raises privacy and security concerns for the users as their conversations can be recorded and relayed to the cloud without their knowledge. Recent studies have shown that the visual gaze plays an important role when interacting with conservation agents such as VAs, and users tend to turn their heads or body toward the VA when invoking it. In this paper, we propose a device-free, non-obtrusive acoustic sensing system called HeadTalk to thwart the misactivation of VAs. The proposed system leverages the user's head direction information and verifies that a human generates the sound to minimize accidental activations. Our extensive evaluation shows that HeadTalk can accurately infer a speaker's head orientation with an average accuracy of 96.14% and distinguish human voice from a mechanical speaker with an equal error rate of 2.58%. We also conduct a user interaction study to assess how users perceive our proposed approach compared to existing privacy controls. Our results suggest that HeadTalk can not only enhance the security and privacy controls for VAs but do so in a usable way without requiring any additional hardware.}, journal={2023 53RD ANNUAL IEEE/IFIP INTERNATIONAL CONFERENCE ON DEPENDABLE SYSTEMS AND NETWORKS, DSN}, author={Zhang, Shaohu and Sabir, Aafaq and Das, Anupam}, year={2023}, pages={597–610} }
 @article{sabir_lafontaine_das_2022, title={Hey Alexa, Who Am I Talking to?: Analyzing Users' Perception and Awareness Regarding Third-party Alexa Skills}, DOI={10.1145/3491102.3517510}, abstractNote={The Amazon Alexa voice assistant provides convenience through automation and control of smart home appliances using voice commands. Amazon allows third-party applications known as skills to run on top of Alexa to further extend Alexa’s capability. However, as multiple skills can share the same invocation phrase and request access to sensitive user data, growing security and privacy concerns surround third-party skills. In this paper, we study the availability and effectiveness of existing security indicators or a lack thereof to help users properly comprehend the risk of interacting with different types of skills. We conduct an interactive user study (inviting active users of Amazon Alexa) where participants listen to and interact with real-world skills using the official Alexa app. We find that most participants fail to identify the skill developer correctly (i.e., they assume Amazon also develops the third-party skills) and cannot correctly determine which skills will be automatically activated through the voice interface. We also propose and evaluate a few voice-based skill type indicators, showcasing how users would benefit from such voice-based indicators.}, journal={PROCEEDINGS OF THE 2022 CHI CONFERENCE ON HUMAN FACTORS IN COMPUTING SYSTEMS (CHI' 22)}, author={Sabir, Aafaq and Lafontaine, Evan and Das, Anupam}, year={2022} }
 @article{lafontaine_sabir_das_2021, title={Understanding People's Attitude and Concerns towards Adopting IoT Devices}, DOI={10.1145/3411763.3451633}, abstractNote={The proliferation of the Internet of Things (IoT) has started transforming our lifestyle through automation of home appliances. However, there are users who are hesitant to adopt IoT devices due to various privacy and security concerns. In this paper, we elicit peoples’ attitude and concerns towards adopting IoT devices. We conduct an online survey and collect responses from 232 participants from three different geographic regions (United States, Europe, and India); the participants consist of both adopters and non-adopters of IoT devices. Through data analysis, we determine that there are both similarities and differences in perceptions and concerns between adopters and non-adopters. For example, even though IoT and non-IoT users share similar security and privacy concerns, IoT users are more comfortable using IoT devices in private settings compared to non-IoT users. Furthermore, when comparing users’ attitude and concerns across different geographic regions, we found similarities between participants from the US and Europe, yet participants from India showcased contrasting behavior. For instance, we found that participants from India were more trusting in their government to properly protect consumer data and were more comfortable using IoT devices in a variety of public settings, compared to participants from the US and Europe. Based on our findings, we provide recommendations to reduce users’ concerns in adopting IoT devices, and thereby enhance user trust towards adopting IoT devices.}, journal={EXTENDED ABSTRACTS OF THE 2021 CHI CONFERENCE ON HUMAN FACTORS IN COMPUTING SYSTEMS (CHI'21)}, author={Lafontaine, Evan and Sabir, Aafaq and Das, Anupam}, year={2021} }